Book Image

Azure Synapse Analytics Cookbook

By : Gaurav Agarwal, Meenakshi Muralidharan
Book Image

Azure Synapse Analytics Cookbook

By: Gaurav Agarwal, Meenakshi Muralidharan

Overview of this book

As data warehouse management becomes increasingly integral to successful organizations, choosing and running the right solution is more important than ever. Microsoft Azure Synapse is an enterprise-grade, cloud-based data warehousing platform, and this book holds the key to using Synapse to its full potential. If you want the skills and confidence to create a robust enterprise analytical platform, this cookbook is a great place to start. You'll learn and execute enterprise-level deployments on medium-to-large data platforms. Using the step-by-step recipes and accompanying theory covered in this book, you'll understand how to integrate various services with Synapse to make it a robust solution for all your data needs. Whether you're new to Azure Synapse or just getting started, you'll find the instructions you need to solve any problem you may face, including using Azure services for data visualization as well as for artificial intelligence (AI) and machine learning (ML) solutions. By the end of this Azure book, you'll have the skills you need to implement an enterprise-grade analytical platform, enabling your organization to explore and manage heterogeneous data workloads and employ various data integration services to solve real-time industry problems.
Table of Contents (11 chapters)

Working with serverless SQL pool

Azure Synapse Analytics has serverless SQL pool endpoints that are primarily used to query data in Azure Data Lake (Parquet, Delta Lake, delimited text formats), Azure Cosmos DB, and Dataverse.

We can access the data using T-SQL queries without the need to copy and load data in a SQL store through serverless SQL pool. Serverless SQL pool is ideally a wrapper service for interactive querying and distributed data processing for large-scale analysis of big data systems. It is a completely serverless and managed service offering from Microsoft Azure, built with fault tolerance, high reliability, and high performance for larger datasets.

Serverless SQL pool is suitable for the following scenarios:

  • Basic exploration and discovery where data in Azure Data Lake Storage (ADLS)with different formats such as Parquet, CSV, Delta, and JSON can be used to derive insights.
  • A relational abstraction layer on top of raw data without transformation,...